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Articles 3991 - 4020 of 8619
Full-Text Articles in Engineering
Board # 273: Nsf Iuse Hsi Implementation And Evaluation Project: The Freshman Year Innovator Experience (Fyie): Bridging The Urm Gap In Stem., Noe Vargas Hernandez, Javier A. Ortega, Arturo A. Fuentes, Eleazar Marquez, Ming-Tsan Lu
Board # 273: Nsf Iuse Hsi Implementation And Evaluation Project: The Freshman Year Innovator Experience (Fyie): Bridging The Urm Gap In Stem., Noe Vargas Hernandez, Javier A. Ortega, Arturo A. Fuentes, Eleazar Marquez, Ming-Tsan Lu
Mechanical Engineering Faculty Publications
The University of X's Freshman Year Innovator Experience (FYIE) program, hosted at a Minority Serving Institution (MSI), seeks to improve the first-year experience for new students by nurturing essential academic success skills. Specifically tailored to freshman mechanical engineering students, the program aims to equip them with self-transformation skills to navigate through the amplified academic and professional obstacles brought about by the COVID-19 pandemic. Participants of FYIE engage in two concurrent courses: Introduction to Engineering (Course A) and Learning Frameworks (Course B). In Course A, students undertake a 6-week engineering design project, while in Course B, they work on a 6-week …
Range-Dependent Meso-Scale Geoacoustic Seabed Quantification, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso
Range-Dependent Meso-Scale Geoacoustic Seabed Quantification, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso
Electrical and Computer Engineering Faculty Publications and Presentations
This study presents a probabilistic one-step two-dimensional (2D) inversion method of spherical-wave reflection coefficient data to estimate the range-dependent structure and geoacoustic parameters along a track. The approach of inverting such datasets independently as one-dimensional (1D) layered models and merging them to a 2D section is feasible but computationally expensive. This study demonstrates a more parsimonious 2D parametrization for active source data recorded on a towed hydrophone array. The comparison of data variance reduction for 1D- and 2D-based results clearly favors the 2D parametrization described here.
Analyzing Player Difficulty Perception In Platformers Through Procedural Level Generation, Sasank Madineni
Analyzing Player Difficulty Perception In Platformers Through Procedural Level Generation, Sasank Madineni
Master's Theses
Games utilizing Procedural Level Generation (PLG), such as Roguelikes, are becoming increasingly popular in today's gaming sphere. In games employing PLG, levels are generated randomly or pseudo-randomly, and aim to retain player attention through variance in levels between playthroughs. However, when generating levels with variance in structure and design, player enjoyment is often a mixed bag. With low enjoyment, player retention for these games can dwindle. This study explores the efficacy of real-time difficulty adjustment in procedurally generated platformers, as a method for maintaining stable player enjoyment without causing frustration. This thesis focuses on creating a short user experience, MIMEVA, …
Hybrid Computing For Real-Time Model Predictive Control Of A Buck Converter, Grace Paladichuk
Hybrid Computing For Real-Time Model Predictive Control Of A Buck Converter, Grace Paladichuk
Master's Theses
Advancements in power electronics require high switching frequencies which the digital control routines of the systems cannot keep up with. Analog computing is added to digital control systems to prevent bottlenecks and allow real-time implementation. This paper proposes a hybrid computing model predictive control system for a buck converter. The control system implements the gradient dynamics of the optimization function using digital computing, and the gradient dynamics for the penalty function and integrator using analog computing. For the full simulations of the entire system, the PLECS RT Box is used to simulate the controller in real time with a 1 …
Bentonite Erosion And Cation Exchange Effects On Hydraulic Conductivity Of Geosynthetic Clay Liners, Grace Paananen
Bentonite Erosion And Cation Exchange Effects On Hydraulic Conductivity Of Geosynthetic Clay Liners, Grace Paananen
Master's Theses
Geosynthetic clay liners (GCLs) are used in municipal solid waste landfill (MSW) liner and cover systems as an alternative to thick compacted clay layers. Previous field studies have revealed potential for bentonite erosion in GCLs when subjected to wet-dry cycles that occur when GCLs are placed on slopes, covered with a geomembrane, and left exposed without additional soil cover. A laboratory test program was conducted to quantify the effects of bentonite erosion on hydraulic conductivity of sodium-bentonite geosynthetic clay liners and samples subjected to cation exchange treatment in addition to bentonite erosion. This test program determined what level of bentonite …
A Neutrosophic And Q-Rung Orthopair Fuzzy Sets Approach For Desertification Susceptibility Mapping: A Case Study In Matrouh, Egypt, Nabil M. Abdelaziz, Khalid A. Eldrandaly, Amira M. Fawzy, Gehan A. Fouad, Safa Al-Saeed
A Neutrosophic And Q-Rung Orthopair Fuzzy Sets Approach For Desertification Susceptibility Mapping: A Case Study In Matrouh, Egypt, Nabil M. Abdelaziz, Khalid A. Eldrandaly, Amira M. Fawzy, Gehan A. Fouad, Safa Al-Saeed
Neutrosophic Systems with Applications
This study introduces an innovative approach to desertification susceptibility mapping by integrating q-rung orthopair fuzzy sets (Q-ROFS) with a neutrosophic environment. Conducted in Matrouh, Egypt, the research quantifies desertification risk through advanced modeling techniques that address uncertainty and non-linearity in environmental data. The Q-ROFS framework enhances risk prediction by capturing complex relationships among desertification indicators. Neutrosophic logic, meanwhile, effectively addresses imprecision and ambiguity. The resulting susceptibility map clearly distinguishes between vulnerable and non-vulnerable regions, offering valuable guidance for policymakers and planners. The analysis revealed that approximately 79.98% of the study area falls under moderate susceptibility, 14.27% under high susceptibility, and …
A Proposed Mathematical Framework For Fuzzy It Service Management (F-Itsm) And Neutrosophic It Service Management (N-Itsm), Takaaki Fujita
A Proposed Mathematical Framework For Fuzzy It Service Management (F-Itsm) And Neutrosophic It Service Management (N-Itsm), Takaaki Fujita
Neutrosophic Systems with Applications
Fuzzy sets, rough sets, hyperrough sets, intuitionistic fuzzy sets, neutrosophic sets, plithogenic sets , and other frameworks for handling uncertainty are under active research every day. These concepts can model a wide range of real-world phenomena and are frequently investigated to facilitate more efficient decision-making. IT Service Management is a systematic approach to designing, delivering, managing, and improving IT services in alignment with organizational objectives. In this paper, we explore the Mathematical Frameworks for Fuzzy IT Service Management (F-ITSM) and Neutrosophic IT Service Management (N-ITSM), which combine these uncertainty-based ideas with IT Service Management practices.
A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods, Muhammad Aslam, Abdulrahman Alaita, Florentin Smarandache
A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods, Muhammad Aslam, Abdulrahman Alaita, Florentin Smarandache
Neutrosophic Systems with Applications
Neutrosophic statistical analysis has gained attention for incorporating the degree of indeterminacy when analyzing imprecise and interval data under uncertainty–-an aspect often overlooked by classical statistics, fuzzy statistical analysis, and interval statistics. Recently, critical discussions have emerged regarding the use and applications of neutrosophic statistics, with some questioning its usefulness and validity. In this paper, we present a critical assessment of the existing literature, focusing on areas where misunderstandings and misinterpretations of neutrosophic statistical methods have occurred. We also examine flawed comparisons made between the results of neutrosophic statistics and interval statistics. Furthermore, substantial issues have been identified in the …
Biostride - Prosthetic Charging Stand, Abigael Howard, Brett Matich, Allie Mcauliffe, Liam Harwood
Biostride - Prosthetic Charging Stand, Abigael Howard, Brett Matich, Allie Mcauliffe, Liam Harwood
Biomedical Engineering
This Final Report outlines the development of a lower limb prosthetic docking and charging station to address a critical need for individuals with unilateral transfemoral amputations who use microprocessor-controlled prosthetics. This project is focused on designing and producing a secure, accessible, and aesthetically pleasing stand to store and charge prosthetic limbs overnight, targeting the lack of commercially available, functional prosthetic storage. The absence of a functional storage solution points to a failure in meaningfully addressing the human needs of prosthetics users, exacerbating user frustration through the perpetuation of issues including prosthetics falling over into inaccessible positions, and tripping hazards due …
Force Mapping Wand For Individuals With Upper-Limb Amputations, Max Bosse, Cole Capitani, Eddie Grassini
Force Mapping Wand For Individuals With Upper-Limb Amputations, Max Bosse, Cole Capitani, Eddie Grassini
Biomedical Engineering
Technology relating to upper-limb amputations has seen many advances in recent years, especially in terms of function and aesthetic appeal. Although these improvements exist, comfort is often a primary concern among prosthetic users and can lead to prosthetic abandonment [1]. Without a standardized method of measuring force concentrations in patients, high rates of discomfort and potential tissue damage remain. The goal of this project is to create a force mapping system for upper-limb amputees to help minimize discomfort in socket fit during the fitting process using real-time data and software to view force concentrations. To accomplish this goal, background research …
The Weaving Of Machine Learning And Artificial Intelligence Into The Fabric Of Cybersecurity Curriculum: From Degree Plan To Capstone Projects, Mahmoud K. Quweider, Liyu Zhang, Jorge Castillo, Ala Qubbaj
The Weaving Of Machine Learning And Artificial Intelligence Into The Fabric Of Cybersecurity Curriculum: From Degree Plan To Capstone Projects, Mahmoud K. Quweider, Liyu Zhang, Jorge Castillo, Ala Qubbaj
Informatics and Engineering Systems Faculty Publications
As our newly designed degree in Cybersecurity enters its fourth year, students in the program are starting to take courses beyond the basic ones, including senior courses, technical electives, and capstone projects. While Cybersecurity is at the heart of our degree that addresses the national need for cybersecurity specialists, how we approach the education and pedagogy of cybersecurity in the era of Big Data and AI/ML (Artificial Intelligence/Machine Learning) is a question that we are addressing in real-time as techniques and measures and countermeasures of cybersecurity attacks keep evolving and taking advantages of the rapid advancements in computing, memory, storage, …
Optimized Electrocoagulation Pre-Treatment For Fouling Reduction During Nanofiltration Of Lake Water Containing Microcystin-Lr, Thomas Mckean, Chidambaram Tharmaraiselvan, Sarah Do, S. Ranil Wickramasinghe
Optimized Electrocoagulation Pre-Treatment For Fouling Reduction During Nanofiltration Of Lake Water Containing Microcystin-Lr, Thomas Mckean, Chidambaram Tharmaraiselvan, Sarah Do, S. Ranil Wickramasinghe
Chemical Engineering Faculty Publications and Presentations
Microcystin-LR (MCLR) is a toxin produced by harmful algal blooms that is emerging as a threat to drinking and recreational water systems worldwide. Nanofiltration (NF) is an effective technique for purifying contaminated water sources; however, membrane fouling caused by coexisting organic matter limits the practicality of the process. This research studies the use of an electrocoagulation (EC) pretreatment to limit fouling during the NF process. Water for this study was taken from Lake Fayetteville, a local body of water where MCLR concentrations have been recorded to be >15 µg/L. EC was performed using polyaluminum chloride as a background electrolyte at …
Load Balancing In Mobile Networks Using Deep Reinforcement Learning And Traffic Prediction, Shorouk Raafat Mokhtar Abouamasha
Load Balancing In Mobile Networks Using Deep Reinforcement Learning And Traffic Prediction, Shorouk Raafat Mokhtar Abouamasha
Theses and Dissertations
Wireless communication networks are advancing at a rapid pace, driven by various challenges and ambitious goals. This rapid growth is driven by a range of applications, including technologies like the Internet of Things (IoT), as well as innovations in smart cities, autonomous vehicles, and more. Different applications demand specific performance criteria such as high data throughput, low latency, robust reliability, and efficient energy usage. In this thesis, we investigate two enhancements that can be adopted in wireless networks to tackle the challenges of resource optimization and network management. The motivation behind this is the fact that future networks will face …
Addressing Urban Traffic Congestion: A Deep Reinforcement Learning-Based Approach, Tairan Liu
Addressing Urban Traffic Congestion: A Deep Reinforcement Learning-Based Approach, Tairan Liu
Mineta Transportation Institute
In an innovative venture, the research team embarked on a mission to redefine urban traffic flow by introducing an automated way to manage traffic light timings. This project integrates two critical technologies, Deep Q-Networks (DQN) and Auto-encoders, into reinforcement learning, with the goal of making traffic smoother and reducing the all-too-common road congestion in simulated city environments. Deep Q-Networks (DQN) are a form of reinforcement learning algorithms that learns the best actions to take in various situations through trial and error. Auto-encoders, on the other hand, are tools that help simplify complex data, making it easier for the DQN to …
Nsf Eec: Establishing Utrgv’S Center For Broadening Participation In Engineering: Engage, Educate, Enrich, Ala Qubbaj, Laura Benitez, Noe Vargas Hernandez, Constantine Tarawneh, Arturo A. Fuentes, Nazmul Islam, Edna Orozco-Leonhardt, Thuy Vu, Angela M. Chapman
Nsf Eec: Establishing Utrgv’S Center For Broadening Participation In Engineering: Engage, Educate, Enrich, Ala Qubbaj, Laura Benitez, Noe Vargas Hernandez, Constantine Tarawneh, Arturo A. Fuentes, Nazmul Islam, Edna Orozco-Leonhardt, Thuy Vu, Angela M. Chapman
Mechanical Engineering Faculty Publications
Hispanics are one of the fastest growing populations in the US, yet they are underrepresented in engineering. University of Texas Rio Grande Valley (UTRGV), a major Hispanic Serving Institution (HSI) with a student population over 95% Hispanic, is well-positioned to address this disparity. UTRGV established a Center for Broadening Participation in Engineering: Engage, Educate, Enrich (CBPE-E3) to enhance Hispanic participation in engineering from early awareness through professional employment. The CBPE -E3 aims to increase enrollment, retention, and advancement rates of Hispanic students in higher education engineering, especially Latinas facing intersectional barriers of race and gender. The CBPE -E3 envisions becoming …
I-280/Wolfe Road Interchange Redesign, Mitchell Wong, Dave Liang
I-280/Wolfe Road Interchange Redesign, Mitchell Wong, Dave Liang
Civil, Environmental and Sustainable Engineering Senior Theses
With the increasing population, there is an increasing need for traffic efficiency and road safety. Roadways that were once considered adequate may be unable to accommodate the growing number of vehicles on the road. In this paper, we analyze the I-280/Wolfe Road Interchange to determine its safety and efficiency inadequacies and propose an improved interchange design to fix these issues. Our analysis reveals that there is room for improvement in the safety of drivers, bikers, and pedestrians, as well as opportunities to enhance the efficiency of sections of the road that require it. We identified the lack of protective barriers …
Ni-Mn-In Heusler Alloy Ribbon For Magnetocaloric Application, Bao Nguyen
Ni-Mn-In Heusler Alloy Ribbon For Magnetocaloric Application, Bao Nguyen
Masters Theses
A traditional cooling system, which applies compression technology within the working fluid, has had a lot of negative impacts on the environment and has low efficiency. They have almost reached the thermodynamic efficiency; there is little room for further improvement. Therefore, solid-state cooling systems, especially those that use the magnetocaloric effect (MCE), have drawnmuch interest as an alternative solution for the vapor-compression system. The Heusler alloy, especially Ni-Mn-In in this research, can be an excellent candidate for this application due to its unique properties, such as the shape memory effect and giant MCE. Their giant MCE results from a first-order …
Sustainable Disposal Of Pecan Shells, Jose Carlos Carrasco
Sustainable Disposal Of Pecan Shells, Jose Carlos Carrasco
Open Access Theses & Dissertations
Urbanization acceleration has increased the consumption of natural resources and carbon footprint, pushing the need for sustainable development. Even though various construction materials are needed for infrastructure development, the most commonly used material is Ordinary Portland Cement for strength (OPC) and durability, while sand is used as a filler in the mixes prepared with OPC. The main goal of this study is to find a sustainable substitute for sand, which is locally available and currently being placed in landfills. One such material is pecan shells, and a thorough analysis of the literature led us to investigate the possible use of …
Hunting, Feiyang Zhuang
Hunting, Feiyang Zhuang
Masters Theses
This writing is about fragility and revelation of technological systems. It considers how brokenness, delay, and opacity are not flaws but openings—opportunities to reimagine our relationship to technology as something grounded, sensory, and continuous with the natural and material world.
Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz
Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz
Dissertations
Reducing the size, weight, power consumption, and cost (SWaP-C) of infrared detectors could make infrared sensing more widely accessible. In the critical mid-wavelength infrared (MWIR) spectral range of 3-5 gm, commercially available detectors are limited by the high costs associated with epitaxial growth and hybridization, as well as the need for cryogenic cooling. These factors restrict their use to defense and space applications.
Colloidal quantum dots present a promising material for overcoming these challenges, with wafer-scale monolithic integration and Auger suppression being the key material capabilities to minimize the sensor's SWaP-C. Infrared sensors based on colloidal quantum dots have been …
Childhood Neuroanatomical Markers Of Familial And Nonfamilial Attention-Deficit/Hyperactivity Disorder, Rahman Baboli
Childhood Neuroanatomical Markers Of Familial And Nonfamilial Attention-Deficit/Hyperactivity Disorder, Rahman Baboli
Dissertations
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder, characterized by developmentally inappropriate levels of inattention, hyperactivity, and impulsivity. Children with family history of ADHD are at an elevated risk of having ADHD as well as a higher risk of persistent ADHD into adulthood, reflecting a source of etiological heterogeneity in ADHD. This heterogeneity in terms of both biological and environmental risk factors may explain differences in neural correlates, outcomes, cognitive, behavioral as well as developmental trajectories. It is therefore critical to understand the influence of having, or not having positive family risk factors on the neuroanatomical structures of the …
Machine Learning And Optimization For Intelligent Decision-Making, Elson Cibaku
Machine Learning And Optimization For Intelligent Decision-Making, Elson Cibaku
Dissertations
This dissertation presents a series of innovative machine learning and optimization model designs that address complex operational challenges across logistics and power systems. By integrating advanced neural architectures with robust optimization techniques, the work delivers scalable solutions designed to improve efficiency, reliability, and decision-making in dynamic and real-world environments. The first study introduces a two-stage approach to effective vaccine distribution. This framework tackles the capacitated vehicle routing problem by combining adaptive clustering techniques with reinforcement learning and a simulated annealing pickup policy. Through extensive computational experiments, the approach demonstrates substantial improvements in routing efficiency, reducing both computational time and logistical …
Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan
Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan
Dissertations
This dissertation presents a comprehensive automated framework for power converter design, leveraging reinforcement learning (RL) and graph-transformer networks (GTN) to address critical inefficiencies in traditional manual topology optimization. Motivated by the combinatorial increase of circuit design spaces and the computational cost of iterative simulations, this work develops a robust framework for generating energy-efficient topologies requiring rapid and reliable circuit design.
The framework integrates three key components: (1) an upper-confidence-bound-tree-based (UCT-based) RL model for circuit topology space exploration, (2) parallelized UCT algorithms to accelerate exploration processes, (3) a Graph-Transformer-based Network enabling fast circuit performance evaluation. Experimental validation demonstrates the whole framework …
The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine
Dissertations
Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.
This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …
Modulation Of Cerebellar Cells By Transcranial Ac Stimulation In Anesthetized Rats, Qi Kang
Modulation Of Cerebellar Cells By Transcranial Ac Stimulation In Anesthetized Rats, Qi Kang
Dissertations
Noninvasive brain stimulation (NIBS) is increasingly utilized in clinical trials for the treatment of neurological disorders. Each NIBS technique offers distinct advantages. Transcranial electrical stimulation (tES) is easy to apply and requires only simple equipment, while transcranial magnetic stimulation (TMS) can penetrate deeper than tES into the brain and it is more focal. Transcranial focused ultrasound stimulation (FUS) is superior to both in terms of penetration and focal stimulation. This study focuses on the modulation of the cerebellum, traditionally believed to be associated with motor coordination but increasingly recognized for its role in cognition and emotion as well. While tES …
Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal
Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal
Dissertations
Artificial intelligence (AI) has achieved remarkable performances across various domains. In most real-world applications, data often takes relational forms, such as graphs and networks, or sequential forms, such as text and time series. As AI evolves, specialized models have emerged to handle these structures; Graph Neural Networks (GNNs) for relational mining and Large Language Models (LLMs) for sequential understanding. Despite their success, these models face challenges in security, robustness, and interpretability. GNNs excel in relational reasoning but are vulnerable to adversarial manipulation and lack interpretability, while LLMs are strong in linguistic reasoning and generalization yet struggle with relational data and …
An Inquiry Into The Physics Of Mixing And Floc Filtration, Andrew P. Pennock
An Inquiry Into The Physics Of Mixing And Floc Filtration, Andrew P. Pennock
Dissertations
Flocculation and clarification are two essential processes to deliver safe water at a reasonable cost to consumers. There are two major thrusts to the research presented in this dissertation. The first is to better characterize the physics and mixing parameters used for the design of hydraulic flocculators in the context of drinking water treatment plants. The second major thrust is to investigate floc filtration as a mechanism for the removal of primary particles during floc blanket clarification.
The intensity of mixing in environmental and chemical engineering applications is often characterized by the Camp and Stein velocity gradient. This parameter has …
Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado
Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado
Dissertations
Mixed reality (MR) and augmented reality (AR) systems are reshaping digital experiences by seamlessly integrating physical and virtual environments. This dissertation presents a comprehensive framework for next-generation immersive systems, combining advances in real-time data processing, multi-user synchronization, and secure communication. The core contributions are structured around three interconnected systems: MediVerse, TeleAvatar, and MultiAvatarLink, each addressing critical challenges in mobile MR.
MediVerse is a secure and scalable framework for real-time health and performance monitoring, integrating intelligent IoT sensors, wearable technologies, and MR interfaces. It supports multi-camera fusion, adaptive compression, and real-time three-dimensional (3D) point cloud generation, enhancing data accuracy and responsiveness …
A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke
A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
In this research, a System of Systems (SoS) meta-architecture is conceptualized to design a digital platform-based system framework for the distribution of domestic workers to boost the crowd-sourced economy. While an Object Process Methodology (OPM) is used to articulate the relationships between the objects and functions, a Design Structure Matrix (DSM) has been applied to address the interactions between individual components to categorize them into subsystems to create the SoS architecture. This SoS architecture incorporates several Key Performance Attributes (KPAs) and Key Performance Parameters (KPPs) to systematically evaluate the meta-architectures. The Analytical Hierarchical Process (AHP), Pugh’s Evaluation Matrix, and Technique …
The Prospect Of Geospatial Analysis In The Prediction Of Surface Quality In Machining, Prithbey Raj Dey, David Lee Enke
The Prospect Of Geospatial Analysis In The Prediction Of Surface Quality In Machining, Prithbey Raj Dey, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
This research underscores the prospect of geospatial analysis in machining operations to enhance precise prediction and robustness, offering a comprehensive framework of spatial modeling for advanced manufacturing processes. Geospatial analysis not only provides accurate predictions but also estimates the uncertainty associated with these predictions, offering valuable insights for process optimization. The surface quality in the machining processes is expressed by the estimation of the average surface roughness. While machining parameters are extensively analyzed for their influence on surface quality, the roughness profile parameters are inadequately explored. This work integrates these underexplored parameters into geospatial predictive models and evaluates their impact …